Using real-time trace data to predict collaboration quality and creative fluency in design teams

Ninger Zhou, Lorraine Kisselburgh, Senthil Chandrasegaran, S. Karthik Badam, Niklas Elmqvist, Kylie Peppler, Karthik Ramani

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)

Abstract

In this study, sixteen Engineering students were assigned to small groups (n=4) to work collaboratively on engineering design tasks. Using wearable sociometric devices, we collected real-time non-linguistic speech data on team interaction including turn-taking, successful interrupts and overlaps. Results from 2-stage regression models indicate that speech and conversational dynamics such as turn-taking and successful interrupts are significant in predicting the perceived collaboration quality and creative fluency of design teams.

Original languageEnglish
Title of host publication11th International Conference on Computer Supported Collaborative Learning
Subtitle of host publicationExploring the Material Conditions of Learning
EditorsOskar Lindwall, Paivi Hakkinen, Timothy Koschmann, Pierre Tchounikine, Sten Ludvigsen
PublisherInternational Society of the Learning Sciences (ISLS)
Pages831-832
Number of pages2
ISBN (Electronic)9780990355076
Publication statusPublished - 2015
Externally publishedYes
Event11th International Conference on Computer Supported Collaborative Learning: Exploring the Material Conditions of Learning, CSCL 2015 - Gothenburg, Sweden
Duration: 7 Jun 201511 Jun 2015

Publication series

NameComputer-Supported Collaborative Learning Conference, CSCL
Volume2
ISSN (Print)1573-4552

Conference

Conference11th International Conference on Computer Supported Collaborative Learning: Exploring the Material Conditions of Learning, CSCL 2015
CountrySweden
CityGothenburg
Period7/06/1511/06/15

Keywords

  • Collaboration quality
  • Creativity
  • Design learning
  • Sociometrics

Fingerprint

Dive into the research topics of 'Using real-time trace data to predict collaboration quality and creative fluency in design teams'. Together they form a unique fingerprint.

Cite this